Influence of sample size on permeability of carbon–carbon composites with stochastic microstructure

IF 8.1 2区材料科学 Q1 ENGINEERING, MANUFACTURING

Composites Part A: Applied Science and Manufacturing Pub Date : 2025-06-17 DOI:10.1016/j.compositesa.2025.109126

T. Lavaggi , J.W. Gillespie Jr. , P.D. Mulye , C. Binetruy , S.G. Advani

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引用次数: 0

Abstract

Permeability is one of the key parameters for the successful densification of carbon–carbon composites (CCC), as it governs the ability of the matrix precursor to infiltrate the porous carbonized structure. Unlike the case of traditional dry fiber preforms, such as continuous or woven textiles, which exhibit a periodic microstructure having a relatively small representative volume element (RVE), the microstructure of pyrolyzed CCC is far more complex. In CCC a periodic fabric architecture is combined with a matrix that is highly stochastic exhibiting a broad distribution of pore sizes and a network of interconnected transverse cracks within tows and delaminations between layers that extend beyond the fabric intrinsic RVE dimensions. For accurate permeability measurements, the size of a statistically homogenous RVE must be determined.

In this study, a T800SC 12K 2 x 2 twill weave fabric (RVE size 25 mm²) with MT35700 benzoxazine resin is pyrolyzed to form CCC with 57 % fiber volume fraction and 20 % porosity measured in a previous study. The effect of the sample size on the effective permeability of the pore network developed during pyrolysis for cross-ply laminates having 5 and 33 layers is investigated. The results of experiments on samples of different in-plane dimensions, ranging from 400 to 2000 mm², are compared to numerical simulations of permeability using 70 full-thickness high-resolution computed-tomography (CT) images, with in-plane dimensions of 1.80 by 1.97 mm², as the statistical description of the geometry of the porous microstructure. Monte Carlo simulations are performed on numerical models of the 5 and 33 ply laminates of in-plane dimensions ranging from about 3.5 mm² to 35000 mm². This procedure is used to identify the minimum size of the statistical representative volume element (sRVE) of the CCC microstructure. For a coefficient of variation of 5 %, the size of the sRVE was determined to be 350 mm² for the sample of 5 plies and 130 mm² for the sample of 33 plies. In both cases the sRVE is significantly larger than the RVE of the twill weave. The predicted effective permeability on the sRVE is found to be in agreement with the experimental permeability.

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样品尺寸对随机微观结构碳-碳复合材料渗透率的影响

渗透率是碳-碳复合材料致密化的关键参数之一，它决定了基体前驱体渗透多孔碳化结构的能力。与传统的干纤维预成型（如连续或机织纺织品）不同，其表现出具有相对较小的代表性体积元（RVE）的周期性微观结构，热解CCC的微观结构要复杂得多。在CCC中，周期性织物结构与高度随机的矩阵相结合，显示出广泛的孔隙大小分布和在拖中相互连接的横向裂缝网络，以及超出织物固有RVE尺寸的层之间的分层。为了精确测量渗透率，必须确定统计上均匀的RVE的大小。在本研究中，将T800SC 12K 2 × 2斜纹织物（RVE尺寸为25mm2）与MT35700苯并嗪树脂进行热解，形成具有57%纤维体积分数和20%孔隙率的CCC。研究了样品尺寸对5层和33层交叉层合板热解过程中孔隙网络有效渗透率的影响。将不同面内尺寸（400 ~ 2000 mm2）样品的实验结果与70张全层高分辨率计算机断层扫描（CT）图像的渗透率数值模拟结果进行了比较，其中面内尺寸为1.80 × 1.97 mm2，作为多孔微观结构几何形状的统计描述。对5层和33层板的数值模型进行了蒙特卡罗模拟，其面内尺寸范围从约3.5 mm2到35000 mm2。该程序用于确定CCC微观结构的统计代表性体积元（sRVE）的最小尺寸。对于5%的变异系数，确定5层样品的sRVE尺寸为350 mm2, 33层样品的sRVE尺寸为130 mm2。在这两种情况下，sRVE都明显大于斜纹织物的RVE。结果表明，预测的储层有效渗透率与实验渗透率基本一致。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Composites Part A: Applied Science and Manufacturing 工程技术-材料科学：复合

CiteScore

15.20

自引率

5.70%

发文量

492

审稿时长

30 days

期刊介绍： Composites Part A: Applied Science and Manufacturing is a comprehensive journal that publishes original research papers, review articles, case studies, short communications, and letters covering various aspects of composite materials science and technology. This includes fibrous and particulate reinforcements in polymeric, metallic, and ceramic matrices, as well as 'natural' composites like wood and biological materials. The journal addresses topics such as properties, design, and manufacture of reinforcing fibers and particles, novel architectures and concepts, multifunctional composites, advancements in fabrication and processing, manufacturing science, process modeling, experimental mechanics, microstructural characterization, interfaces, prediction and measurement of mechanical, physical, and chemical behavior, and performance in service. Additionally, articles on economic and commercial aspects, design, and case studies are welcomed. All submissions undergo rigorous peer review to ensure they contribute significantly and innovatively, maintaining high standards for content and presentation. The editorial team aims to expedite the review process for prompt publication.